NVIDIA Tesla P4

NVIDIA Tesla P4

NVIDIA Tesla P4 is a Professional video accelerator from NVIDIA. It began to be released in September 2016. The GPU has a boost frequency of 1114MHz. It also has a memory frequency of 1502MHz. Its characteristics, as well as benchmark results, are presented in more detail below.

Basic

Label Name
NVIDIA
Platform
Professional
Launch Date
September 2016
Model Name
Tesla P4
Generation
Tesla
Base Clock
886MHz
Boost Clock
1114MHz
Shading Units
?
The most fundamental processing unit is the Streaming Processor (SP), where specific instructions and tasks are executed. GPUs perform parallel computing, which means multiple SPs work simultaneously to process tasks.
2560
SM Count
?
Multiple Streaming Processors (SPs), along with other resources, form a Streaming Multiprocessor (SM), which is also referred to as a GPU's major core. These additional resources include components such as warp schedulers, registers, and shared memory. The SM can be considered the heart of the GPU, similar to a CPU core, with registers and shared memory being scarce resources within the SM.
20
Transistors
7,200 million
TMUs
?
Texture Mapping Units (TMUs) serve as components of the GPU, which are capable of rotating, scaling, and distorting binary images, and then placing them as textures onto any plane of a given 3D model. This process is called texture mapping.
160
L1 Cache
48 KB (per SM)
L2 Cache
2MB
Bus Interface
PCIe 3.0 x16
Foundry
TSMC
Process Size
16 nm
Architecture
Pascal
TDP
75W

Memory Specifications

Memory Size
8GB
Memory Type
GDDR5
Memory Bus
?
The memory bus width refers to the number of bits of data that the video memory can transfer within a single clock cycle. The larger the bus width, the greater the amount of data that can be transmitted instantaneously, making it one of the crucial parameters of video memory. The memory bandwidth is calculated as: Memory Bandwidth = Memory Frequency x Memory Bus Width / 8. Therefore, when the memory frequencies are similar, the memory bus width will determine the size of the memory bandwidth.
256bit
Memory Clock
1502MHz
Bandwidth
?
Memory bandwidth refers to the data transfer rate between the graphics chip and the video memory. It is measured in bytes per second, and the formula to calculate it is: memory bandwidth = working frequency × memory bus width / 8 bits.
192.3 GB/s

Theoretical Performance

Pixel Rate
?
Pixel fill rate refers to the number of pixels a graphics processing unit (GPU) can render per second, measured in MPixels/s (million pixels per second) or GPixels/s (billion pixels per second). It is the most commonly used metric to evaluate the pixel processing performance of a graphics card.
71.30 GPixel/s
Texture Rate
?
Texture fill rate refers to the number of texture map elements (texels) that a GPU can map to pixels in a single second.
178.2 GTexel/s
FP16 (half)
?
An important metric for measuring GPU performance is floating-point computing capability. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy.
89.12 GFLOPS
FP64 (double)
?
An important metric for measuring GPU performance is floating-point computing capability. Double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy, while single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
178.2 GFLOPS
FP32 (float)
?
An important metric for measuring GPU performance is floating-point computing capability. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
5.479 TFlops

Miscellaneous

Vulkan Version
?
Vulkan is a cross-platform graphics and compute API by Khronos Group, offering high performance and low CPU overhead. It lets developers control the GPU directly, reduces rendering overhead, and supports multi-threading and multi-core processors.
1.3
OpenCL Version
3.0
OpenGL
4.6
DirectX
12 (12_1)
CUDA
6.1
Power Connectors
None
ROPs
?
The Raster Operations Pipeline (ROPs) is primarily responsible for handling lighting and reflection calculations in games, as well as managing effects like anti-aliasing (AA), high resolution, smoke, and fire. The more demanding the anti-aliasing and lighting effects in a game, the higher the performance requirements for the ROPs; otherwise, it may result in a sharp drop in frame rate.
64
Shader Model
6.4
Suggested PSU
250W

FP32 (float)

5.479 TFlops

Blender

437

OctaneBench

91

Compared to Other GPU

SiliconCat Rating

440
Ranks 440 among all GPU on our website
FP32 (float)
Radeon E9550 MXM
AMD, September 2016
5.832 TFlops
Radeon R9 295X2
AMD, April 2014
5.618 TFlops
Tesla P4
NVIDIA, September 2016
5.479 TFlops
GeForce RTX 2070 Max Q
NVIDIA, January 2019
5.35 TFlops
Arc A570M
Intel, August 2023
5.218 TFlops
Blender
Radeon RX 6950 XT
AMD, May 2022
2864
Radeon RX 7600M
AMD, January 2023
1338
GeForce GTX 1070 GDDR5X
NVIDIA, December 2018
561
Tesla P4
NVIDIA, September 2016
437
Radeon Vega 8
AMD, January 2021
62
OctaneBench
TITAN RTX
NVIDIA, December 2018
356
Quadro P6000
NVIDIA, October 2016
181
Tesla P4
NVIDIA, September 2016
91
Quadro M4000
NVIDIA, June 2015
54
Quadro M2000
NVIDIA, April 2016
28